[Characterization of genetic EEG-variations with the amplitude-interval-analysis. III. Assignment of new obtained EEGs to well-known types of bioelectric activities on the basis of data of amplitude-interval-analysis (author's transl)].
Quantitative description of some EEG-variants by amplitude-interval (time-domain) analysis revealed significant differences of parameter means but failed to give one single, sufficiently reliable criterion for classification. Therefore, we tried to solve the problem of classification through quantitative criteria by discriminant analysis. For each EEG, 128 different measurements were taken, but only 104 were included in the analysis; the rest failed to contribute any measurable information. For 243 of th 298 probands, the data were sufficient for inclusion in the study. Only 15 (6.2%) were classified falsely; this number was reduced to 3 (1.7%) when the calculation was performed leaving out the (64) controls. A control analysis by a Monte-Carlo-Method in which the classification criterium was calculated using 80% of all cases only, and the remaining 20% were then attributed tentatively to the variant groups, gave much less convincing results. It follows that more and better criteria for separation of these variants have to be developed before classification of EEGs exclusively on the basis of measurements will become possible.
D004569:Electroencephalography / Q000145:classification*; D005071:Evoked Potentials; D014644:Genetic Variation; D006801:Humans; D013223:Statistics as Topic
Charakterisierung erblicher EEG-Varianten mit Hilfe der Amplituden-Intervall-Analyse. III. Das Klassifizierungsproblem: Zuordnung eines neu abgeleiteten EEG zu einem de bekannten EEG-Typen aufgrund der Parameterwerte der Amplituden-Intervall-Analyse.